Subspace Orthogonal Projection for Texture Segmentation with Wavelet Frames

We propose a new supervised texture segmentation and classification technique based on combining features extracted from the discrete wavelet frames of an image (specifically, the detail images at multiple resolutions) with a nonlinear band generation algorithm and an orthogonal subspace projection operator (OSP). As a supervised technique, the algorithm needs apriori information about the number and location of textures present in the composite texture training images. The OSP operator role is twofold: to extract a set of texture signature vectors each uniquely characterizing only one texture; after that, the texture segmentation process commences and the signature vectors are used to identify/mark textures in new images, essentially a pixel labeling process with all pixels of one texture having the same label. The simulation results show satisfactory classification and segmentation on a set of composite texture images while having good real time performance and moderate storage and ...

• Type: Conference
• Year: 2008
• Where: IADIS
• Authors: Mahmoud K. Quweider
• Keywords: Composite Texture, IADIS 2008, Internet Technology, Supervised Texture Segmentation, Texture Segmentation